Source code for pyuvdata.uvbeam.beamfits

# -*- mode: python; coding: utf-8 -*-
# Copyright (c) 2018 Radio Astronomy Software Group
# Licensed under the 2-clause BSD License

"""Class for reading and writing beamfits files."""
import os
import warnings

import numpy as np
from astropy.io import fits

from .uvbeam import UVBeam
from .. import utils as uvutils

__all__ = ["BeamFITS"]

hpx_primary_ax_nums = {
    "pixel": 1,
    "freq": 2,
    "feed_pol": 3,
    "spw": 4,
    "basisvec": 5,
    "complex": 6,
}
reg_primary_ax_nums = {
    "img_ax1": 1,
    "img_ax2": 2,
    "freq": 3,
    "feed_pol": 4,
    "spw": 5,
    "basisvec": 6,
    "complex": 7,
}

hxp_basisvec_ax_nums = {"pixel": 1, "ncomp": 2, "basisvec": 3}
reg_basisvec_ax_nums = {"img_ax1": 1, "img_ax2": 2, "ncomp": 3, "basisvec": 4}

fits_axisname_dict = {
    "hpx_inds": "PIX_IND",
    "azimuth": "AZIMUTH",
    "zen_angle": "ZENANGLE",
    "zenorth_x": "ZENX-SIN",
    "zenorth_y": "ZENY-SIN",
}


[docs]class BeamFITS(UVBeam): """ Defines a fits-specific subclass of UVBeam for reading and writing beamfits files. This class should not be interacted with directly, instead use the read_beamfits and write_beamfits methods on the UVBeam class. The beamfits format supports regularly gridded or healpix beam files. The format defined here for healpix beams is not compatible with true healpix formats because it needs to support multiple dimensions (e.g. polarization, frequency, efield vectors). """
[docs] def read_beamfits( self, filename, run_check=True, check_extra=True, run_check_acceptability=True, check_auto_power=True, fix_auto_power=True, ): """ Read the data from a beamfits file. Parameters ---------- filename : str The beamfits file to read from. run_check : bool Option to check for the existence and proper shapes of required parameters after reading in the file. check_extra : bool Option to check optional parameters as well as required ones. run_check_acceptabilit : bool Option to check acceptable range of the values of required parameters after reading in the file. check_auto_power : bool For power beams, check whether the auto polarization beams have non-zero imaginary values in the data_array (which should not mathematically exist). fix_auto_power : bool For power beams, if auto polarization beams with imaginary values are found, fix those values so that they are real-only in data_array. """ # update filename attribute basename = os.path.basename(filename) self.filename = [basename] self._filename.form = (1,) with fits.open(filename) as fname: primary_hdu = fname[0] primary_header = primary_hdu.header.copy() hdunames = uvutils._fits_indexhdus(fname) # find the rest of the tables data = primary_hdu.data # only support simple antenna_types for now. # support for phased arrays should be added self._set_simple() self.beam_type = primary_header.pop("BTYPE", None) if self.beam_type is not None: self.beam_type = self.beam_type.lower() else: bunit = primary_header.pop("BUNIT", None) if bunit is not None and bunit.lower().strip() == "jy/beam": self.beam_type = "power" if self.beam_type == "intensity": self.beam_type = "power" n_dimensions = primary_header.pop("NAXIS") ctypes = [ primary_header[ctype].lower() for ctype in (key for key in primary_header if "ctype" in key.lower()) ] self.pixel_coordinate_system = primary_header.pop("COORDSYS", None) if self.pixel_coordinate_system is None: for cs, cs_dict in self.coordinate_system_dict.items(): ax_names = [ fits_axisname_dict[ax].lower() for ax in cs_dict["axes"] ] if ax_names == ctypes[0 : len(ax_names)]: coord_list = ctypes[0 : len(ax_names)] self.pixel_coordinate_system = cs else: ax_names = [ fits_axisname_dict[ax].lower() for ax in self.coordinate_system_dict[self.pixel_coordinate_system][ "axes" ] ] coord_list = ctypes[0 : len(ax_names)] if coord_list != ax_names: raise ValueError( "Coordinate axis list does not match coordinate system" ) if self.pixel_coordinate_system == "healpix": # get pixel values out of HPX_IND extension hpx_hdu = fname[hdunames["HPX_INDS"]] self.Npixels = hpx_hdu.header["NAXIS2"] hpx_data = hpx_hdu.data self.pixel_array = hpx_data["hpx_inds"] ax_nums = hpx_primary_ax_nums self.nside = primary_header.pop("NSIDE", None) self.ordering = primary_header.pop("ORDERING", None) data_Npixels = primary_header.pop("NAXIS" + str(ax_nums["pixel"])) if data_Npixels != self.Npixels: raise ValueError( "Number of pixels in HPX_IND extension does " "not match number of pixels in data array" ) else: ax_nums = reg_primary_ax_nums self.Naxes1 = primary_header.pop("NAXIS" + str(ax_nums["img_ax1"])) self.Naxes2 = primary_header.pop("NAXIS" + str(ax_nums["img_ax2"])) self.axis1_array = uvutils._fits_gethduaxis( primary_hdu, ax_nums["img_ax1"] ) self.axis2_array = uvutils._fits_gethduaxis( primary_hdu, ax_nums["img_ax2"] ) # if units aren't defined they are degrees by FITS convention # convert degrees to radians because UVBeam uses radians axis1_units = primary_header.pop( "CUNIT" + str(ax_nums["img_ax1"]), "deg" ) if axis1_units == "deg": self.axis1_array = np.deg2rad(self.axis1_array) elif axis1_units != "rad": raise ValueError( 'Units of first axis array are not "deg" or "rad".' ) axis2_units = primary_header.pop( "CUNIT" + str(ax_nums["img_ax2"]), "deg" ) if axis2_units == "deg": self.axis2_array = np.deg2rad(self.axis2_array) elif axis2_units != "rad": raise ValueError( 'Units of second axis array are not "deg" or "rad".' ) n_efield_dims = max(ax_nums[key] for key in ax_nums) if self.beam_type == "power": # check for case where the data is complex (e.g. for xy beams) if n_dimensions > ax_nums["complex"] - 1: complex_arrs = np.split(data, 2, axis=0) self.data_array = np.squeeze( complex_arrs[0] + 1j * complex_arrs[1], axis=0 ) else: self.data_array = data # Note: This axis is called STOKES by analogy with the equivalent # uvfits axis # However, this is confusing because it is NOT a true Stokes axis, # it is really the polarization axis. if ( primary_header.pop("CTYPE" + str(ax_nums["feed_pol"])) .lower() .strip() == "stokes" ): self.Npols = primary_header.pop("NAXIS" + str(ax_nums["feed_pol"])) self.polarization_array = np.int32( uvutils._fits_gethduaxis(primary_hdu, ax_nums["feed_pol"]) ) self._set_power() elif self.beam_type == "efield": self._set_efield() if n_dimensions < n_efield_dims: raise ValueError( "beam_type is efield and data dimensionality is too low" ) complex_arrs = np.split(data, 2, axis=0) self.data_array = np.squeeze( complex_arrs[0] + 1j * complex_arrs[1], axis=0 ) if ( primary_header.pop("CTYPE" + str(ax_nums["feed_pol"])) .lower() .strip() == "feedind" ): self.Nfeeds = primary_header.pop("NAXIS" + str(ax_nums["feed_pol"])) feedlist = primary_header.pop("FEEDLIST", None) if feedlist is not None: self.feed_array = np.array(feedlist[1:-1].split(", ")) else: raise ValueError( "Unknown beam_type: {type}, beam_type should be " '"efield" or "power".'.format(type=self.beam_type) ) self.data_normalization = primary_header.pop("NORMSTD", None) self.telescope_name = primary_header.pop("TELESCOP") self.feed_name = primary_header.pop("FEED", None) self.feed_version = primary_header.pop("FEEDVER", None) self.model_name = primary_header.pop("MODEL", None) self.model_version = primary_header.pop("MODELVER", None) self.x_orientation = primary_header.pop("XORIENT", None) self.interpolation_function = primary_header.pop("INTERPFN", None) self.freq_interp_kind = primary_header.pop("FINTERP", None) # shapes if ( primary_header.pop("CTYPE" + str(ax_nums["freq"])).lower().strip() == "freq" ): self.Nfreqs = primary_header.pop("NAXIS" + str(ax_nums["freq"])) if n_dimensions > ax_nums["spw"] - 1: if ( primary_header.pop("CTYPE" + str(ax_nums["spw"])).lower().strip() == "if" ): self.Nspws = primary_header.pop("NAXIS" + str(ax_nums["spw"]), None) # subtract 1 to be zero-indexed self.spw_array = ( uvutils._fits_gethduaxis(primary_hdu, ax_nums["spw"]) - 1 ) if n_dimensions > ax_nums["basisvec"] - 1: if ( primary_header.pop("CTYPE" + str(ax_nums["basisvec"])) .lower() .strip() == "vecind" ): self.Naxes_vec = primary_header.pop( "NAXIS" + str(ax_nums["basisvec"]), None ) if ( self.Nspws is None or self.Naxes_vec is None ) and self.beam_type == "power": if self.Nspws is None: self.Nspws = 1 self.spw_array = np.array([0]) if self.Naxes_vec is None: self.Naxes_vec = 1 # add extra empty dimensions to data_array as appropriate while len(self.data_array.shape) < n_efield_dims - 1: self.data_array = np.expand_dims(self.data_array, axis=0) self.freq_array = uvutils._fits_gethduaxis(primary_hdu, ax_nums["freq"]) self.freq_array.shape = (self.Nspws,) + self.freq_array.shape # default frequency axis is Hz, but check for corresonding CUNIT freq_units = primary_header.pop("CUNIT" + str(ax_nums["freq"]), "Hz") if freq_units != "Hz": freq_factor = {"kHz": 1e3, "MHz": 1e6, "GHz": 1e9} if freq_units in freq_factor.keys(): self.freq_array = self.freq_array * freq_factor[freq_units] else: raise ValueError("Frequency units not recognized.") self.history = str(primary_header.get("HISTORY", "")) if not uvutils._check_history_version( self.history, self.pyuvdata_version_str ): self.history += self.pyuvdata_version_str self.extra_keywords = uvutils._get_fits_extra_keywords(primary_header) # read BASISVEC HDU if present if "BASISVEC" in hdunames: basisvec_hdu = fname[hdunames["BASISVEC"]] basisvec_header = basisvec_hdu.header self.basis_vector_array = basisvec_hdu.data if self.pixel_coordinate_system == "healpix": basisvec_ax_nums = hxp_basisvec_ax_nums if ( basisvec_header["CTYPE" + str(basisvec_ax_nums["pixel"])] .lower() .strip() != "pix_ind" ): raise ValueError( "First axis in BASISVEC HDU must be 'Pix_Ind' for " "healpix beams" ) basisvec_Npixels = basisvec_header.pop( "NAXIS" + str(basisvec_ax_nums["pixel"]) ) if basisvec_Npixels != self.Npixels: raise ValueError( "Number of pixels in BASISVEC HDU does not match " "primary HDU" ) else: basisvec_ax_nums = reg_basisvec_ax_nums basisvec_coord_list = [ basisvec_header[ "CTYPE" + str(basisvec_ax_nums["img_ax1"]) ].lower(), basisvec_header[ "CTYPE" + str(basisvec_ax_nums["img_ax2"]) ].lower(), ] basisvec_axis1_array = uvutils._fits_gethduaxis( basisvec_hdu, basisvec_ax_nums["img_ax1"] ) basisvec_axis2_array = uvutils._fits_gethduaxis( basisvec_hdu, basisvec_ax_nums["img_ax2"] ) # if units aren't defined they are degrees by FITS convention # convert degrees to radians because UVBeam uses radians axis1_units = basisvec_header.pop( "CUNIT" + str(basisvec_ax_nums["img_ax1"]), "deg" ) if axis1_units == "deg": basisvec_axis1_array = np.deg2rad(basisvec_axis1_array) elif axis1_units != "rad": raise ValueError( "Units of first axis array in BASISVEC HDU are not" " 'deg' or 'rad'." ) axis2_units = basisvec_header.pop( "CUNIT" + str(basisvec_ax_nums["img_ax2"]), "deg" ) if axis2_units == "deg": basisvec_axis2_array = np.deg2rad(basisvec_axis2_array) elif axis2_units != "rad": raise ValueError( "Units of second axis array in BASISVEC HDU are not" " 'deg' or 'rad'." ) if not np.all(basisvec_axis1_array == self.axis1_array): raise ValueError( "First image axis in BASISVEC HDU does not match " "primary HDU" ) if not np.all(basisvec_axis2_array == self.axis2_array): raise ValueError( "Second image axis in BASISVEC HDU does not " "match primary HDU" ) if basisvec_coord_list != coord_list: raise ValueError( "Pixel coordinate list in BASISVEC HDU does not " "match primary HDU" ) basisvec_Naxes_vec = basisvec_header[ "NAXIS" + str(basisvec_ax_nums["basisvec"]) ] self.Ncomponents_vec = basisvec_header[ "NAXIS" + str(basisvec_ax_nums["ncomp"]) ] basisvec_cs = basisvec_header["COORDSYS"] if basisvec_cs != self.pixel_coordinate_system: raise ValueError( "Pixel coordinate system in BASISVEC HDU does " "not match primary HDU" ) if basisvec_Naxes_vec != self.Naxes_vec: raise ValueError( "Number of vector coordinate axes in BASISVEC " "HDU does not match primary HDU" ) # check to see if BANDPARM HDU exists and read it out if it does if "BANDPARM" in hdunames: bandpass_hdu = fname[hdunames["BANDPARM"]] bandpass_header = bandpass_hdu.header.copy() self.reference_impedance = bandpass_header.pop("ref_imp", None) freq_data = bandpass_hdu.data columns = [c.name for c in freq_data.columns] self.bandpass_array = freq_data["bandpass"] self.bandpass_array = self.bandpass_array[np.newaxis, :] if "rx_temp" in columns: self.receiver_temperature_array = freq_data["rx_temp"] self.receiver_temperature_array = self.receiver_temperature_array[ np.newaxis, : ] if "loss" in columns: self.loss_array = freq_data["loss"] self.loss_array = self.loss_array[np.newaxis, :] if "mismatch" in columns: self.mismatch_array = freq_data["mismatch"] self.mismatch_array = self.mismatch_array[np.newaxis, :] if "s11" in columns: s11 = freq_data["s11"] s12 = freq_data["s12"] s21 = freq_data["s21"] s22 = freq_data["s22"] self.s_parameters = np.zeros((4, 1, len(s11))) self.s_parameters[0, 0, :] = s11 self.s_parameters[1, 0, :] = s12 self.s_parameters[2, 0, :] = s21 self.s_parameters[3, 0, :] = s22 else: # no bandpass information, set it to an array of ones self.bandpass_array = np.zeros((self.Nspws, self.Nfreqs)) + 1.0 if run_check: self.check( check_extra=check_extra, run_check_acceptability=run_check_acceptability, check_auto_power=check_auto_power, fix_auto_power=fix_auto_power, )
[docs] def write_beamfits( self, filename, run_check=True, check_extra=True, run_check_acceptability=True, check_auto_power=True, fix_auto_power=False, clobber=False, ): """ Write the data to a beamfits file. Parameters ---------- filename : str The beamfits file to write to. run_check : bool Option to check for the existence and proper shapes of required parameters before writing the file. check_extra : bool Option to check optional parameters as well as required ones. run_check_acceptability : bool Option to check acceptable range of the values of required parameters before writing the file. check_auto_power : bool For power beams, check whether the auto polarization beams have non-zero imaginary values in the data_array (which should not mathematically exist). fix_auto_power : bool For power beams, if auto polarization beams with imaginary values are found, fix those values so that they are real-only in data_array. clobber : bool Option to overwrite the filename if the file already exists. """ if run_check: self.check( check_extra=check_extra, run_check_acceptability=run_check_acceptability, check_auto_power=check_auto_power, fix_auto_power=fix_auto_power, ) if self.antenna_type != "simple": raise ValueError( "This beam fits writer currently only supports " "simple (rather than phased array) antenna beams" ) if self.Nfreqs > 1: freq_spacing = self.freq_array[0, 1:] - self.freq_array[0, :-1] if not uvutils._test_array_constant(freq_spacing, self._freq_array.tols): raise ValueError( "The frequencies are not evenly spaced (probably " "because of a select operation). The beamfits format " "does not support unevenly spaced frequencies." ) freq_spacing = freq_spacing[0] else: freq_spacing = 1 if self.pixel_coordinate_system == "healpix": ax_nums = hpx_primary_ax_nums else: ax_nums = reg_primary_ax_nums if self.Naxes1 > 1: if not uvutils._test_array_constant_spacing(self._axis1_array): raise ValueError( "The pixels are not evenly spaced along first axis. " "The beam fits format does not support " "unevenly spaced pixels." ) axis1_spacing = self.axis1_array[1] - self.axis1_array[0] else: axis1_spacing = 1 if self.Naxes2 > 1: if not uvutils._test_array_constant_spacing(self._axis2_array): raise ValueError( "The pixels are not evenly spaced along second axis. " "The beam fits format does not support " "unevenly spaced pixels." ) axis2_spacing = self.axis2_array[1] - self.axis2_array[0] else: axis2_spacing = 1 primary_header = fits.Header() # Conforming to fits format primary_header["SIMPLE"] = True primary_header["BITPIX"] = 32 primary_header["BTYPE"] = self.beam_type primary_header["NORMSTD"] = self.data_normalization primary_header["COORDSYS"] = self.pixel_coordinate_system # metadata primary_header["TELESCOP"] = self.telescope_name primary_header["FEED"] = self.feed_name primary_header["FEEDVER"] = self.feed_version primary_header["MODEL"] = self.model_name primary_header["MODELVER"] = self.model_version if self.x_orientation is not None: primary_header["XORIENT"] = self.x_orientation if self.interpolation_function is not None: primary_header["INTERPFN"] = ( self.interpolation_function, "interpolation function", ) if self.freq_interp_kind is not None: primary_header["FINTERP"] = ( self.freq_interp_kind, "frequency " "interpolation kind (scipy interp1d)", ) if self.beam_type == "efield": primary_header["FEEDLIST"] = "[" + ", ".join(self.feed_array) + "]" if self.pixel_coordinate_system == "healpix": primary_header["NSIDE"] = self.nside primary_header["ORDERING"] = self.ordering # set up pixel axis primary_header["CTYPE" + str(ax_nums["pixel"])] = ( "Pix_Ind", "Index into pixel array in HPX_INDS extension.", ) primary_header["CRVAL" + str(ax_nums["pixel"])] = 1 primary_header["CRPIX" + str(ax_nums["pixel"])] = 1 primary_header["CDELT" + str(ax_nums["pixel"])] = 1 else: # set up first image axis # FITs standard is to use degrees (not radians as in the UVBeam object) deg_axis1_array = np.rad2deg(self.axis1_array) deg_axis1_spacing = np.rad2deg(axis1_spacing) primary_header["CTYPE" + str(ax_nums["img_ax1"])] = fits_axisname_dict[ self.coordinate_system_dict[self.pixel_coordinate_system]["axes"][0] ] primary_header["CRVAL" + str(ax_nums["img_ax1"])] = deg_axis1_array[0] primary_header["CRPIX" + str(ax_nums["img_ax1"])] = 1 primary_header["CDELT" + str(ax_nums["img_ax1"])] = deg_axis1_spacing primary_header["CUNIT" + str(ax_nums["img_ax1"])] = "deg" # set up second image axis deg_axis2_array = np.rad2deg(self.axis2_array) deg_axis2_spacing = np.rad2deg(axis2_spacing) primary_header["CTYPE" + str(ax_nums["img_ax2"])] = fits_axisname_dict[ self.coordinate_system_dict[self.pixel_coordinate_system]["axes"][1] ] primary_header["CRVAL" + str(ax_nums["img_ax2"])] = deg_axis2_array[0] primary_header["CRPIX" + str(ax_nums["img_ax2"])] = 1 primary_header["CDELT" + str(ax_nums["img_ax2"])] = deg_axis2_spacing primary_header["CUNIT" + str(ax_nums["img_ax2"])] = "deg" # set up frequency axis primary_header["CTYPE" + str(ax_nums["freq"])] = "FREQ" primary_header["CUNIT" + str(ax_nums["freq"])] = "Hz" primary_header["CRVAL" + str(ax_nums["freq"])] = self.freq_array[0, 0] primary_header["CRPIX" + str(ax_nums["freq"])] = 1 primary_header["CDELT" + str(ax_nums["freq"])] = freq_spacing # set up feed or pol axis if self.beam_type == "power": if self.Npols > 1: if not uvutils._test_array_constant_spacing(self._polarization_array): raise ValueError( "The polarization values are not evenly " "spaced (probably because of a select operation). " "The uvfits format does not support unevenly " "spaced polarizations." ) pol_spacing = self.polarization_array[1] - self.polarization_array[0] else: pol_spacing = 1 # Note: This axis is called STOKES by analogy with the equivalent # uvfits axis # However, this is confusing because it is NOT a true Stokes axis, # it is really the polarization axis. primary_header["CTYPE" + str(ax_nums["feed_pol"])] = ( "STOKES", "Polarization integers, see uvbeam memo", ) primary_header[ "CRVAL" + str(ax_nums["feed_pol"]) ] = self.polarization_array[0] primary_header["CDELT" + str(ax_nums["feed_pol"])] = pol_spacing # handle case where data_array is complex (e.g. for xy beams) if np.iscomplexobj(self.data_array): primary_data = np.concatenate( [ np.expand_dims(self.data_array.real, axis=0), np.expand_dims(self.data_array.imag, axis=0), ], axis=0, ) else: primary_data = self.data_array elif self.beam_type == "efield": primary_header["CTYPE" + str(ax_nums["feed_pol"])] = ( "FEEDIND", 'Feed: index into "FEEDLIST".', ) primary_header["CRVAL" + str(ax_nums["feed_pol"])] = 1 primary_header["CDELT" + str(ax_nums["feed_pol"])] = 1 primary_data = np.concatenate( [ np.expand_dims(self.data_array.real, axis=0), np.expand_dims(self.data_array.imag, axis=0), ], axis=0, ) else: raise ValueError( "Unknown beam_type: {type}, beam_type should be " '"efield" or "power".'.format(type=self.beam_type) ) primary_header["CRPIX" + str(ax_nums["feed_pol"])] = 1 # set up spw axis primary_header["CTYPE" + str(ax_nums["spw"])] = ( "IF", "Spectral window number.", ) primary_header["CUNIT" + str(ax_nums["spw"])] = "Integer" primary_header["CRVAL" + str(ax_nums["spw"])] = 1 primary_header["CRPIX" + str(ax_nums["spw"])] = 1 primary_header["CDELT" + str(ax_nums["spw"])] = 1 # set up basis vector axis primary_header["CTYPE" + str(ax_nums["basisvec"])] = ( "VECIND", "Basis vector index.", ) primary_header["CUNIT" + str(ax_nums["basisvec"])] = "Integer" primary_header["CRVAL" + str(ax_nums["basisvec"])] = 1 primary_header["CRPIX" + str(ax_nums["basisvec"])] = 1 primary_header["CDELT" + str(ax_nums["basisvec"])] = 1 if np.iscomplexobj(self.data_array): # set up complex axis primary_header["CTYPE" + str(ax_nums["complex"])] = ( "COMPLEX", "real, imaginary", ) primary_header["CRVAL" + str(ax_nums["complex"])] = 1 primary_header["CRPIX" + str(ax_nums["complex"])] = 1 primary_header["CDELT" + str(ax_nums["complex"])] = 1 # end standard keywords; begin user-defined keywords for key, value in self.extra_keywords.items(): # header keywords have to be 8 characters or less if len(str(key)) > 8: warnings.warn( "key {key} in extra_keywords is longer than 8 " "characters. It will be truncated to 8 as required " "by the uvfits file format.".format(key=key) ) keyword = key[:8].upper() if isinstance(value, (dict, list, np.ndarray)): raise TypeError( "Extra keyword {keyword} is of {keytype}. " "Only strings and numbers are " "supported in uvfits.".format(keyword=key, keytype=type(value)) ) if keyword == "COMMENT": for line in value.splitlines(): primary_header.add_comment(line) else: primary_header[keyword] = value for line in self.history.splitlines(): primary_header.add_history(line) primary_hdu = fits.PrimaryHDU(data=primary_data, header=primary_header) hdulist = fits.HDUList([primary_hdu]) if self.basis_vector_array is not None: basisvec_header = fits.Header() basisvec_header["EXTNAME"] = "BASISVEC" basisvec_header["COORDSYS"] = self.pixel_coordinate_system if self.pixel_coordinate_system == "healpix": basisvec_ax_nums = hxp_basisvec_ax_nums # set up pixel axis basisvec_header["CTYPE" + str(basisvec_ax_nums["pixel"])] = ( "Pix_Ind", "Index into pixel array in HPX_INDS extension.", ) basisvec_header["CRVAL" + str(basisvec_ax_nums["pixel"])] = 1 basisvec_header["CRPIX" + str(basisvec_ax_nums["pixel"])] = 1 basisvec_header["CDELT" + str(basisvec_ax_nums["pixel"])] = 1 else: basisvec_ax_nums = reg_basisvec_ax_nums # set up first image axis basisvec_header[ "CTYPE" + str(basisvec_ax_nums["img_ax1"]) ] = fits_axisname_dict[ self.coordinate_system_dict[self.pixel_coordinate_system]["axes"][0] ] basisvec_header[ "CRVAL" + str(basisvec_ax_nums["img_ax1"]) ] = deg_axis1_array[0] basisvec_header["CRPIX" + str(basisvec_ax_nums["img_ax1"])] = 1 basisvec_header[ "CDELT" + str(basisvec_ax_nums["img_ax1"]) ] = deg_axis1_spacing basisvec_header["CUNIT" + str(basisvec_ax_nums["img_ax1"])] = "deg" # set up second image axis basisvec_header[ "CTYPE" + str(basisvec_ax_nums["img_ax2"]) ] = fits_axisname_dict[ self.coordinate_system_dict[self.pixel_coordinate_system]["axes"][1] ] basisvec_header[ "CRVAL" + str(basisvec_ax_nums["img_ax2"]) ] = deg_axis2_array[0] basisvec_header["CRPIX" + str(basisvec_ax_nums["img_ax2"])] = 1 basisvec_header[ "CDELT" + str(basisvec_ax_nums["img_ax2"]) ] = deg_axis2_spacing basisvec_header["CUNIT" + str(basisvec_ax_nums["img_ax2"])] = "deg" # set up vector component axis (length Ncomponents_vec) basisvec_header["CTYPE" + str(basisvec_ax_nums["ncomp"])] = ( "COMPIND", "Vector component index", ) basisvec_header["CUNIT" + str(basisvec_ax_nums["ncomp"])] = "Integer" basisvec_header["CRVAL" + str(basisvec_ax_nums["ncomp"])] = 1 basisvec_header["CRPIX" + str(basisvec_ax_nums["ncomp"])] = 1 basisvec_header["CDELT" + str(basisvec_ax_nums["ncomp"])] = 1 # set up vector coordinate system axis (length Naxis_vec) basisvec_header["CTYPE" + str(basisvec_ax_nums["basisvec"])] = ( "VECCOORD", "Basis vector index", ) basisvec_header["CUNIT" + str(basisvec_ax_nums["basisvec"])] = "Integer" basisvec_header["CRVAL" + str(basisvec_ax_nums["basisvec"])] = 1 basisvec_header["CRPIX" + str(basisvec_ax_nums["basisvec"])] = 1 basisvec_header["CDELT" + str(basisvec_ax_nums["basisvec"])] = 1 basisvec_data = self.basis_vector_array basisvec_hdu = fits.ImageHDU(data=basisvec_data, header=basisvec_header) hdulist.append(basisvec_hdu) if self.pixel_coordinate_system == "healpix": # make healpix pixel number column. 'K' format indicates 64-bit integer c1 = fits.Column(name="hpx_inds", format="K", array=self.pixel_array) coldefs = fits.ColDefs([c1]) hpx_hdu = fits.BinTableHDU.from_columns(coldefs) hpx_hdu.header["EXTNAME"] = "HPX_INDS" hdulist.append(hpx_hdu) # check for frequency-specific optional arrays. If they're not None, # add them to the BANDPARM binary table HDU along with the bandpass_array bandpass_col = fits.Column( name="bandpass", format="D", array=self.bandpass_array[0, :] ) col_list = [bandpass_col] if self.receiver_temperature_array is not None: rx_temp_col = fits.Column( name="rx_temp", format="D", array=self.receiver_temperature_array[0, :] ) col_list.append(rx_temp_col) if self.loss_array is not None: loss_col = fits.Column(name="loss", format="D", array=self.loss_array[0, :]) col_list.append(loss_col) if self.mismatch_array is not None: mismatch_col = fits.Column( name="mismatch", format="D", array=self.mismatch_array[0, :] ) col_list.append(mismatch_col) if self.s_parameters is not None: s11_col = fits.Column( name="s11", format="D", array=self.s_parameters[0, 0, :] ) s12_col = fits.Column( name="s12", format="D", array=self.s_parameters[1, 0, :] ) s21_col = fits.Column( name="s21", format="D", array=self.s_parameters[2, 0, :] ) s22_col = fits.Column( name="s22", format="D", array=self.s_parameters[3, 0, :] ) col_list += [s11_col, s12_col, s21_col, s22_col] coldefs = fits.ColDefs(col_list) bandpass_hdu = fits.BinTableHDU.from_columns(coldefs) bandpass_hdu.header["EXTNAME"] = "BANDPARM" if self.reference_impedance is not None: bandpass_hdu.header["ref_imp"] = self.reference_impedance hdulist.append(bandpass_hdu) hdulist.writeto(filename, overwrite=clobber) hdulist.close()